CN117117356B - Energy storage battery pack thermal runaway monitoring and tracing method and system - Google Patents
Energy storage battery pack thermal runaway monitoring and tracing method and system Download PDFInfo
- Publication number
- CN117117356B CN117117356B CN202311378203.XA CN202311378203A CN117117356B CN 117117356 B CN117117356 B CN 117117356B CN 202311378203 A CN202311378203 A CN 202311378203A CN 117117356 B CN117117356 B CN 117117356B
- Authority
- CN
- China
- Prior art keywords
- information
- air pressure
- temperature
- thermal runaway
- traceability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004146 energy storage Methods 0.000 title claims abstract description 156
- 238000012544 monitoring process Methods 0.000 title claims abstract description 75
- 238000000034 method Methods 0.000 title claims abstract description 43
- 239000007789 gas Substances 0.000 claims description 250
- 238000004458 analytical method Methods 0.000 claims description 72
- 238000004364 calculation method Methods 0.000 claims description 30
- 238000012549 training Methods 0.000 claims description 23
- 238000001514 detection method Methods 0.000 claims description 22
- 238000012163 sequencing technique Methods 0.000 claims description 14
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 8
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 5
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 5
- 239000001569 carbon dioxide Substances 0.000 claims description 5
- 229910002091 carbon monoxide Inorganic materials 0.000 claims description 5
- 229910052739 hydrogen Inorganic materials 0.000 claims description 5
- 239000001257 hydrogen Substances 0.000 claims description 5
- 125000004435 hydrogen atom Chemical class [H]* 0.000 claims 1
- 238000012360 testing method Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 5
- 238000012896 Statistical algorithm Methods 0.000 description 3
- 150000002431 hydrogen Chemical class 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012983 electrochemical energy storage Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000000670 limiting effect Effects 0.000 description 2
- PQXKHYXIUOZZFA-UHFFFAOYSA-M lithium fluoride Chemical compound [Li+].[F-] PQXKHYXIUOZZFA-UHFFFAOYSA-M 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
- KLARSDUHONHPRF-UHFFFAOYSA-N [Li].[Mn] Chemical compound [Li].[Mn] KLARSDUHONHPRF-UHFFFAOYSA-N 0.000 description 1
- BNOODXBBXFZASF-UHFFFAOYSA-N [Na].[S] Chemical compound [Na].[S] BNOODXBBXFZASF-UHFFFAOYSA-N 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 229910001416 lithium ion Inorganic materials 0.000 description 1
- FUJCRWPEOMXPAD-UHFFFAOYSA-N lithium oxide Chemical compound [Li+].[Li+].[O-2] FUJCRWPEOMXPAD-UHFFFAOYSA-N 0.000 description 1
- 229910001947 lithium oxide Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000004454 trace mineral analysis Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4207—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells for several batteries or cells simultaneously or sequentially
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4285—Testing apparatus
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- General Chemical & Material Sciences (AREA)
- Secondary Cells (AREA)
Abstract
The invention provides a thermal runaway monitoring and tracing method and a thermal runaway monitoring and tracing system for an energy storage battery pack, which relate to the technical field of battery packs, and comprise the following steps: and when the second judging result is yes, extracting time information that the temperature or the air pressure of the plurality of battery units reaches the temperature threshold or the air pressure threshold, obtaining a plurality of first tracing grades and second tracing grades, calculating tracing grades of the plurality of battery units, outputting tracing results, solving the technical problem that the thermal runaway of the energy storage battery unit is easy to occur due to the lack of management and control of the thermal runaway of the energy storage battery unit in the prior art, realizing accurate monitoring tracing of the thermal runaway of the energy storage battery unit, and reducing the occurrence of the thermal runaway of the energy storage battery unit.
Description
Technical Field
The invention relates to the technical field of battery packs, in particular to a thermal runaway monitoring and tracing method and system for an energy storage battery pack.
Background
With the rapid development of the energy storage industry, there is also a great risk involved. According to incomplete statistics, over 30 electrochemical energy storage power station safety accidents occur in the whole world in the last ten years, most of the safety accidents occur in the last 5 years, and the electrochemical energy storage safety situation is not optimistic.
Although the cause of the fire of the energy storage power station is numerous, the thermal runaway of the battery and the thermal runaway diffusion of the battery module and the system are focuses of current attention of the industry, and meanwhile, the technical problem that the thermal runaway of the energy storage battery is easy to occur due to the fact that the thermal runaway of the energy storage battery is lack of control in the prior art.
Disclosure of Invention
The application provides a thermal runaway monitoring and tracing method and system for an energy storage battery pack, which are used for controlling the thermal runaway of the energy storage battery pack aiming at solving the technical problem that the thermal runaway of the energy storage battery pack is easy to occur due to the lack in the prior art.
In view of the above problems, the present application provides a thermal runaway monitoring and tracing method and system for an energy storage battery pack.
In a first aspect, the present application provides a thermal runaway monitoring and tracing method for an energy storage battery pack, the method comprising: based on a thermal runaway monitoring module and a thermal runaway judging module, acquiring temperature information and gas information of a plurality of battery power supplies in an energy storage battery pack through a temperature sensor array and a gas sensor array, and judging the hidden danger of the thermal runaway according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases; when the first judging result is yes, collecting a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window; according to the temperature information sequences and the air pressure information sequences in the air information sequences, performing early-stage matching judgment of thermal runaway according to a preset temperature change trend and a preset air pressure change trend, and obtaining a second judgment result; when the second judging result is yes, extracting time information that the temperature or the air pressure of the plurality of battery cells reaches the temperature threshold or the air pressure threshold and a plurality of temperature information sequences and a plurality of matching degrees of the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend through a thermal runaway tracing module, and carrying out thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades; extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings; and calculating and obtaining the tracing ratings of the battery units based on the first tracing ratings and the second tracing ratings, and outputting tracing results according to the tracing ratings.
In a second aspect, the present application provides an energy storage battery thermal runaway monitoring traceability system, the system comprising: the first judging module is used for acquiring temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack through the temperature sensor array and the gas sensor array based on the thermal runaway monitoring module and the thermal runaway judging module, and judging potential thermal runaway hazards according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases; the sequence acquisition module is used for acquiring a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window when the first discrimination result is yes; the second judging module is used for carrying out early-stage matching judgment of thermal runaway according to the temperature information sequences and the air pressure information sequences in the air information sequences and the preset temperature change trend and the preset air pressure change trend to obtain a second judging result; the first analysis module is used for extracting time information that the temperature or the air pressure of the plurality of battery units reach the temperature threshold or the air pressure threshold through the thermal runaway tracing module when the second judging result is yes, and a plurality of matching degrees of the plurality of temperature information sequences and the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend, and performing thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades; the second analysis module is used for extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings; and the calculation module is used for calculating and obtaining the traceability ratings of the battery units based on the first traceability ratings and the second traceability ratings and outputting traceability results according to the traceability ratings.
In a third aspect, a computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program: based on a thermal runaway monitoring module and a thermal runaway judging module, acquiring temperature information and gas information of a plurality of battery power supplies in an energy storage battery pack through a temperature sensor array and a gas sensor array, and judging the hidden danger of the thermal runaway according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases; when the first judging result is yes, collecting a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window; according to the temperature information sequences and the air pressure information sequences in the air information sequences, performing early-stage matching judgment of thermal runaway according to a preset temperature change trend and a preset air pressure change trend, and obtaining a second judgment result; when the second judging result is yes, extracting time information that the temperature or the air pressure of the plurality of battery cells reaches the temperature threshold or the air pressure threshold and a plurality of temperature information sequences and a plurality of matching degrees of the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend through a thermal runaway tracing module, and carrying out thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades; extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings; and calculating and obtaining the tracing ratings of the battery units based on the first tracing ratings and the second tracing ratings, and outputting tracing results according to the tracing ratings.
In a fourth aspect, a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of: based on a thermal runaway monitoring module and a thermal runaway judging module, acquiring temperature information and gas information of a plurality of battery power supplies in an energy storage battery pack through a temperature sensor array and a gas sensor array, and judging the hidden danger of the thermal runaway according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases; when the first judging result is yes, collecting a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window; according to the temperature information sequences and the air pressure information sequences in the air information sequences, performing early-stage matching judgment of thermal runaway according to a preset temperature change trend and a preset air pressure change trend, and obtaining a second judgment result; when the second judging result is yes, extracting time information that the temperature or the air pressure of the plurality of battery cells reaches the temperature threshold or the air pressure threshold and a plurality of temperature information sequences and a plurality of matching degrees of the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend through a thermal runaway tracing module, and carrying out thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades; extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings; and calculating and obtaining the tracing ratings of the battery units based on the first tracing ratings and the second tracing ratings, and outputting tracing results according to the tracing ratings.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the application provides a method and a system for monitoring and tracing thermal runaway of an energy storage battery pack, relates to the technical field of battery packs, solves the technical problem that the thermal runaway of the energy storage battery pack is lack of being managed and controlled in the prior art, and causes the thermal runaway of the energy storage battery pack to easily occur, realizes rationalizing and accurately monitoring and tracing the thermal runaway of the energy storage battery pack, and reduces the occurrence of the thermal runaway of the energy storage battery pack.
Drawings
Fig. 1 is a schematic flow chart of a thermal runaway monitoring and tracing method for an energy storage battery pack;
fig. 2 is a schematic diagram of a flow chart of obtaining a plurality of first traceability ratings in an energy storage battery pack thermal runaway monitoring traceability method;
fig. 3 is a schematic diagram of a flow chart of obtaining a plurality of second traceability ratings in an energy storage battery pack thermal runaway monitoring traceability method;
fig. 4 is a schematic structural diagram of a thermal runaway monitoring traceability system of an energy storage battery pack;
fig. 5 is an internal structural diagram of a computer device in one embodiment.
Reference numerals illustrate: the system comprises a first judging module 1, a sequence acquisition module 2, a second judging module 3, a first analysis module 4, a second analysis module 5 and a calculation module 6.
Detailed Description
The application provides a thermal runaway monitoring and tracing method and system for an energy storage battery pack, which are used for solving the technical problem that the thermal runaway of the energy storage battery pack is easily caused by the lack of management and control of the thermal runaway of the energy storage battery pack in the prior art.
Example 1
As shown in fig. 1, an embodiment of the present application provides a thermal runaway monitoring and tracing method for an energy storage battery pack, which is applied to a thermal runaway monitoring and tracing device for an energy storage battery pack, where the device includes a temperature sensor array and a gas sensor array disposed in a plurality of battery cells in the energy storage battery pack, and a thermal runaway monitoring module, a thermal runaway discriminating module and a thermal runaway tracing module, and the method includes:
step A100: based on a thermal runaway monitoring module and a thermal runaway judging module, acquiring temperature information and gas information of a plurality of battery power supplies in an energy storage battery pack through a temperature sensor array and a gas sensor array, and judging the hidden danger of the thermal runaway according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases;
further, step a100 of the present application further includes:
Step A110: continuously acquiring temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack through the temperature sensor array and the gas sensor array, and acquiring gas pressure information in the gas information;
step A120: acquiring a temperature threshold and a barometric pressure threshold based on historical detection data of the energy storage battery pack in an early thermal runaway period;
step a130: and respectively judging whether any one of the temperature information or any one of the air pressure information is greater than or equal to the temperature threshold or the air pressure threshold, and obtaining a first judging result.
In the application, the thermal runaway monitoring and tracing method for the energy storage battery pack is applied to a thermal runaway monitoring and tracing device for the energy storage battery pack, and the device comprises a temperature sensor array and a gas sensor array which are arranged in a plurality of battery cells in the energy storage battery pack, a thermal runaway monitoring module, a thermal runaway judging module and a thermal runaway tracing module.
The method is characterized in that a thermal runaway monitoring module and a thermal runaway judging module are used as a basis, temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack are collected through a temperature sensor array and a gas sensor array, the thermal runaway monitoring module is used for monitoring whether thermal runaway characteristics exist in the energy storage battery pack or not, the thermal runaway judging module is used for judging whether thermal runaway exists in the energy storage battery pack or not, the temperature sensor array is used for collecting and extracting real-time temperature data in the energy storage battery pack after sensing and integrating temperature data in the energy storage battery pack, the gas sensor array is used for collecting and extracting real-time lifting data in the energy storage battery pack after sensing and integrating the gas data in the energy storage battery pack, and the gas sensor array is used for sensing and integrating the gas data in the energy storage battery pack.
Further, temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack are continuously collected through the temperature sensor array and the gas sensor array, the temperature information of the plurality of battery power supplies is determined according to battery properties of the energy storage battery pack, and the temperature information of the energy storage battery pack can be about 300 ℃ if the energy storage battery pack is a sodium-sulfur battery, the temperature information of the energy storage battery pack can be-20 ℃ to 60 ℃ if the energy storage battery pack is a lithium ion battery, the gas information of the plurality of battery power supplies is determined according to different battery principles of the energy storage battery pack, the gas information of the plurality of battery power supplies can be lithium fluoride, lithium oxide, manganese lithium acid and the like, the gas information comprises gas pressure and gas concentration information of a plurality of specified gases, and the gas information is substituted into a gas pressure formula to obtain the gas pressure information in the gas information, further, by collecting historical detection data of early thermal runaway of the energy storage battery pack, determining a temperature threshold and an air pressure threshold of the energy storage battery pack, wherein the temperature threshold and the air pressure threshold are used for judging whether temperature information and air pressure information in the energy storage battery pack reach a threshold of thermal runaway of a battery in the energy storage battery pack, so that the temperature threshold and the air pressure threshold are set according to a critical value of thermal runaway of the battery in the energy storage battery pack, and accordingly, potential hazards of thermal runaway of the energy storage battery pack are judged according to the temperature threshold and the air pressure threshold, namely, whether any one piece of temperature information and any piece of air pressure information in the energy storage battery pack reach the temperature threshold and the air pressure threshold are respectively judged, and accordingly, the judgment result is used as a first judgment result, and the first judgment result can comprise 4 types of data:
Data 1: any one temperature information in the energy storage battery pack does not reach a temperature threshold value, and any one air pressure information does not reach an air pressure threshold value;
data 2: any one temperature information in the energy storage battery pack does not reach a temperature threshold value, and any one air pressure information reaches an air pressure threshold value;
data 3: any one temperature information in the energy storage battery pack reaches a temperature threshold value, and any one air pressure information does not reach an air pressure threshold value;
data 4: any one of the temperature information in the energy storage battery pack reaches a temperature threshold value, and any one of the air pressure information reaches an air pressure threshold value;
and then monitoring and tracing the thermal runaway of the energy storage battery pack as an important reference basis according to the first discrimination result as a later stage.
Step A200: when the first judging result is yes, collecting a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window;
in the application, when the obtained first judging result is yes, any one of the temperature information in the energy storage battery pack reaches the temperature threshold, and any one of the air pressure information reaches the air pressure threshold, which means that the energy storage battery pack has a thermal runaway hidden trouble, so that all batteries contained in the energy storage battery pack need to be sequentially subjected to acquisition of temperature information and air information, information sensing of temperature data sensing can be performed on all battery blocks in the energy storage battery pack through a temperature sensor array arranged on a plurality of battery units in the energy storage battery pack, so as to obtain the temperature information of each battery block in the energy storage battery pack, the temperature information obtained by sensing is arranged according to the arrangement sequence of the battery blocks in the energy storage battery pack, and a plurality of temperature information sequences are obtained,
Further, the gas sensor arrays distributed on the plurality of battery cells in the energy storage battery pack are used for sensing information of gas data of all battery blocks in the energy storage battery pack, so that gas information of each battery block in the energy storage battery pack is obtained, the gas information obtained by sensing is distributed according to the arrangement sequence of the battery blocks in the energy storage battery pack, a plurality of gas information sequences are obtained, and further monitoring and tracing of thermal runaway of the energy storage battery pack are realized.
Step A300: according to the temperature information sequences and the air pressure information sequences in the air information sequences, performing early-stage matching judgment of thermal runaway according to a preset temperature change trend and a preset air pressure change trend, and obtaining a second judgment result;
further, step a300 of the present application further includes:
step a310: based on the temperature information sequences and the air pressure information sequences, adopting a least square method to obtain a plurality of temperature change curves and a plurality of air pressure change curves in a fitting way;
step A320: based on historical detection data of early thermal runaway of the energy storage battery pack, acquiring a plurality of sample temperature information sequences and a plurality of sample air pressure information sequences of the thermal runaway, and calculating to acquire a preset temperature information sequence and a preset air pressure information sequence;
Step a330: fitting to obtain the preset temperature change trend and the preset air pressure change trend based on the preset temperature information sequence and the preset air pressure information sequence;
step A340: calculating the correlation degree of the temperature change curves and the air pressure change curves with the preset temperature change trend and the preset air pressure change trend respectively to obtain a plurality of temperature correlation degree information and a plurality of air pressure correlation degree information, wherein the correlation degree is calculated by the following formula:
;
wherein g is the correlation, M is the number of coordinate points in a temperature change curve or an air pressure change curve,is the temperature value or the air pressure value of the ith coordinate point in the temperature change curve or the air pressure change curve,/>A preset temperature value or a preset air pressure value of an ith coordinate point in a preset temperature change trend or a preset air pressure change trend, < ->And->Is the average temperature value or average air pressure value in the temperature change curve or air pressure change curve, and is preset in the temperature change trend or air pressure change trendAn average preset temperature value or an average preset air pressure value;
step A350: and respectively judging whether any one of the temperature correlation degree information or any one of the air pressure correlation degree information is larger than or equal to a correlation degree threshold value, and obtaining a second judging result.
In the application, in order to more accurately monitor and trace the thermal runaway of the energy storage battery pack, firstly, based on temperature monitoring analysis and air pressure monitoring analysis, a time/temperature coordinate system and a time/air coordinate system are respectively constructed based on the obtained plurality of temperature information sequences and air pressure information sequences in the plurality of air pressure information sequences, and meanwhile, temperature data in the plurality of temperature information sequences and air pressure data in the air pressure information sequences in the plurality of air pressure information sequences are sequentially led into the time/temperature coordinate system and the time/air coordinate system, and after the temperature data and the air temperature data are respectively fitted by adopting a least square method, a plurality of temperature change curves and a plurality of air pressure change curves are obtained.
Further, determining a plurality of sample temperature information sequences and a plurality of sample air pressure information sequences of the energy storage battery pack when the energy storage battery pack is in thermal runaway in a history period according to the extracted historical detection data of the early thermal runaway of the energy storage battery pack, calculating an expected temperature information sequence and an expected air pressure information sequence of the energy storage battery pack according to the change trend of the plurality of sample temperature information sequences and the plurality of sample air pressure information sequences in a plurality of temperature change curves and a plurality of air pressure change curves, and taking the calculation result as a preset temperature information sequence and a preset air pressure information sequence;
The data fitting is performed on the preset temperature information sequence and the preset air pressure information sequence by taking the preset temperature information sequence and the preset air pressure information sequence as basic data, namely a statistical algorithm is applied to the preset temperature information sequence and the preset air pressure information sequence to estimate a group of parameter values corresponding to the preset temperature information sequence and a group of parameter values corresponding to the preset air pressure information sequence, so that the statistical algorithm can describe the data process as accurately as possible, the preset temperature information sequence and the preset air pressure information sequence are matched and fitted to obtain the preset temperature change trend and the preset air pressure change trend, and further, a plurality of temperature change curves, a plurality of air pressure change curves, the preset temperature change trend and the correlation degree of the preset air pressure change trend are calculated through the following formulas:
;
wherein g is the correlation, M is the number of coordinate points in a temperature change curve or an air pressure change curve,is the temperature value or the air pressure value of the ith coordinate point in the temperature change curve or the air pressure change curve,/>A preset temperature value or a preset air pressure value of an ith coordinate point in a preset temperature change trend or a preset air pressure change trend, < ->And->The temperature change curve or the average temperature value or the average air pressure value in the air pressure change curve, and the average preset temperature value or the average preset air pressure value in the preset temperature change trend or the preset air pressure change trend;
The method includes inputting a plurality of temperature change curves, a plurality of air pressure change curves, a preset temperature change trend and a preset air pressure change trend into a formula for calculation, and according to the calculated g, namely a plurality of temperature correlation information and a plurality of air pressure correlation information, the range of the calculated g can be (0, 1), and when g is closer to 1, the calculated g is more relevant, and when g is closer to 0, the calculated g is less relevant, so as to judge whether any one of the plurality of temperature correlation information or any one of the plurality of air pressure correlation information is larger than or equal to a correlation threshold value, wherein the correlation threshold value is set according to thermal runaway monitoring experience, the correlation threshold value can be 0.5, and therefore the judgment result can be used as a second judgment result, and the second judgment result can comprise 4 types of data:
data 1: any one of the plurality of temperature correlation information is smaller than a correlation threshold value, and any one of the plurality of air pressure correlation information is smaller than the correlation threshold value;
data 2: any one of the plurality of temperature correlation information is larger than or equal to a correlation threshold value, and any one of the plurality of air pressure correlation information is smaller than the correlation threshold value;
Data 3: any one of the plurality of temperature correlation information is smaller than the correlation threshold value, and any one of the plurality of air pressure correlation information is larger than or equal to the correlation threshold value;
data 4: any one of the plurality of temperature correlation information is larger than or equal to a correlation threshold value, and any one of the plurality of air pressure correlation information is larger than or equal to the correlation threshold value;
and then the monitoring, tracing and tamping basis for the thermal runaway of the energy storage battery pack is realized for the follow-up according to the second discrimination result.
Step A400: when the second judging result is yes, extracting time information that the temperature or the air pressure of the plurality of battery cells reaches the temperature threshold or the air pressure threshold and a plurality of temperature information sequences and a plurality of matching degrees of the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend through a thermal runaway tracing module, and carrying out thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades;
further, as shown in fig. 2, step a400 of the present application further includes:
step A410: when the second judging result is yes, detecting and judging the time when the temperature or the air pressure of the plurality of battery units reaches the temperature threshold value and the air pressure threshold value through the temperature sensor array and the air sensor array to obtain a plurality of time information, and sequencing according to the sequence from front to back to obtain a plurality of sequencing information;
Step a420: calculating a plurality of temperature information sequences and a plurality of air pressure information sequences, and a plurality of temperature correlation information and a plurality of air pressure correlation information of the preset temperature variation trend and the preset air pressure variation trend;
step a430: weighting calculation is carried out on the temperature correlation information and the air pressure correlation information to obtain matching degrees;
step a440: and performing thermal runaway traceability analysis by combining the plurality of sequencing information and the plurality of matching degrees to obtain a plurality of first traceability ratings.
Further, step a440 of the present application includes:
step a441: acquiring a plurality of sample ordering information sets and a plurality of sample matching degree information sets based on historical monitoring data of thermal runaway of the energy storage battery pack, wherein each sample ordering information set comprises a plurality of sample ordering information of a plurality of sample battery units;
step a442: acquiring a first traceability rating set of a plurality of samples according to the traceability thermal runaway occurrence sequence of the plurality of sample battery cells based on historical traceability detection data of the thermal runaway of the energy storage battery pack;
step A443: a plurality of sample ordering information sets, a plurality of sample matching degree information sets and a plurality of sample first traceability rating sets are adopted as training data to train a converged first traceability analysis channel;
Step a444: and acquiring a plurality of first traceability ratings, and inputting a plurality of sorting information and a plurality of matching degrees into a first traceability analysis channel to acquire.
In this application, in order to better monitor and trace the thermal runaway of the energy storage battery pack, when the obtained second discrimination result is yes, it is considered that any one of the plurality of temperature correlation information is greater than or equal to a correlation threshold, any one of the plurality of air pressure correlation information is greater than or equal to the correlation threshold, at this time, it is required that a thermal runaway tracing module included in the thermal runaway monitoring and tracing device of the energy storage battery pack is used for acquiring the temperature or air pressure of a plurality of battery cells to reach the temperature threshold or the air pressure threshold, and a plurality of temperature information sequences and a plurality of air pressure information sequences are extracted with a plurality of matching degrees of the preset temperature variation trend and the preset air pressure variation trend, and a temperature sensor array and a gas sensor array of a plurality of battery cells in the energy storage battery pack are used for acquiring the temperature parameters and the gas parameters of a plurality of battery cells.
The temperature sensor array and the gas sensor array are used as the basis in the thermal runaway traceability module, the time when the temperature data or the gas pressure data in the energy storage battery pack reaches the temperature threshold value and the gas pressure threshold value is detected, the time length is judged, so that a plurality of time information containing the temperature data and the gas pressure data is obtained, the time information is sequenced according to the sequence from front to back in the time sequence, a plurality of sequencing information of the time information is determined, further, the temperature information sequences and the gas pressure information sequences are calculated based on the sequencing information of the time information, the temperature correlation information and the gas pressure correlation information of the preset temperature change trend and the preset gas pressure change trend are calculated, further, the weighting calculation is carried out on the temperature correlation information and the gas pressure correlation information, the weighting calculation is carried out after the weighting calculation is summarized and accurately determined based on a large amount of data, and the weighting calculation is carried out, and the weighting ratio of the temperature correlation information and the gas pressure correlation information can be a first influence coefficient: and if the second influence coefficient is 4:6, the influence parameters after the weighted calculation process are respectively the first influence parameter 0.4 and the second influence parameter 0.6, a plurality of matching degrees are obtained according to the weighted calculation result, further, the thermal runaway tracing analysis is carried out by combining a plurality of sorting information and a plurality of matching degrees, namely, the obtained historical monitoring data of the thermal runaway of the energy storage battery pack is taken as basic reference data, a plurality of temperature data sorting and a plurality of air pressure data sorting in the historical monitoring data are randomly extracted, meanwhile, the temperature data sorting information and the air pressure data sorting information are determined after being integrated and are recorded as a plurality of sample sorting information sets, the matching degree of the correlation degree in the plurality of temperature data sorting and the matching degree of the correlation degree in the plurality of air pressure data sorting are recorded as a plurality of sample matching degree information sets, and the sample sorting information sets comprise a plurality of sample battery cells.
Meanwhile, according to the tracing thermal runaway occurrence time sequence of the plurality of sample battery cells, tracing detection data in the historical tracing detection data of the thermal runaway of the energy storage battery pack are ordered, a plurality of sample first tracing rating sets are obtained, the tracing rating of the battery cell which is first in the thermal runaway of the energy storage battery pack is regarded as the highest level, the tracing detection data in the historical tracing detection data of the thermal runaway of the energy storage battery pack are ordered in the same way, the ordered data sets are recorded as the plurality of sample first tracing rating sets, further, the plurality of sample ordering information sets, the plurality of sample matching degree information sets and the plurality of sample first tracing rating sets are adopted as training data, the monitoring data are correspondingly set through the training data, the training data are input into the first tracing analysis channel for output monitoring adjustment, when the output result of the first tracing analysis channel is consistent with the monitoring data, the training of the current group is finished, all the training data are finished, and the training of the first tracing analysis channel is finished.
In order to ensure the convergence and accuracy of the first traceability analysis channel, the convergence process may be that when a plurality of sample sorting information sets, a plurality of sample matching degree information sets and a plurality of sample first traceability rating sets in the first traceability analysis channel converge at one point, the convergence is performed when the first traceability analysis channel approaches to a certain value, the accuracy of the first traceability analysis channel may be tested through a test data set, for example, the test accuracy may be set to 80%, and when the test accuracy of the test data set meets 80%, the first traceability analysis channel is constructed.
Finally, a plurality of first tracing grades are obtained by inputting a plurality of sorting information and a plurality of matching degrees into a first tracing analysis channel, so that the monitoring and tracing of the thermal runaway of the energy storage battery pack are realized, and a limiting effect is realized.
Step A500: extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings;
further, as shown in fig. 3, step a500 of the present application further includes:
step A510: extracting and obtaining a plurality of first gas concentration information sequences, a plurality of second gas concentration information sequences and a plurality of third gas concentration information sequences in the plurality of gas information sequences according to the types of the plurality of specified gases, wherein the plurality of specified gases comprise hydrogen, carbon dioxide and carbon monoxide;
step A520: acquiring a first gas concentration information sequence of a sample, a second gas concentration information sequence of the sample and a third gas concentration information sequence of the sample based on historical monitoring data of thermal runaway of the energy storage battery pack;
step a530: fitting to obtain a preset first gas concentration change trend, a preset second gas concentration change trend and a preset third gas concentration change trend based on the sample first gas concentration information sequence, the sample second gas concentration information sequence and the sample third gas concentration information sequence;
Step a540: calculating and obtaining a plurality of first concentration correlation information, a plurality of second concentration correlation information and a plurality of third concentration correlation information of the plurality of first gas concentration information sequences, the plurality of second gas concentration information sequences and the plurality of third gas concentration information sequences by taking the preset first gas concentration change trend, the second gas concentration change trend and the third gas concentration change trend as references, and weighting and calculating to obtain a plurality of concentration correlation information;
step A550: and performing thermal runaway traceability analysis according to the concentration relativity information to obtain a plurality of second traceability ratings.
Further, step a550 of the present application includes:
step A551: acquiring a plurality of sample concentration correlation information sets based on historical monitoring data of thermal runaway of the energy storage battery pack, wherein each sample concentration correlation information set comprises a plurality of sample concentration correlation information of a plurality of sample battery units;
step a552: acquiring a second traceability rating set of a plurality of samples according to the traceability thermal runaway occurrence sequence of the plurality of sample battery cells based on historical traceability detection data of the thermal runaway of the energy storage battery pack;
step A553: the plurality of sample concentration correlation degree information sets and the plurality of sample second traceability rating sets are adopted as training data to train a converged second traceability analysis channel;
Step a554: and acquiring a plurality of second traceability ratings, wherein the plurality of second traceability ratings are acquired by inputting a plurality of concentration relevance information into the second traceability analysis channel.
In the application, in order to monitor and trace the thermal runaway of the energy storage battery pack more accurately, therefore, the trace analysis is needed to be performed on the plurality of battery units by combining the concentration change curves of the plurality of gases with the matching degree of the preset gas concentration change trend curve, so as to improve the accuracy of monitoring and tracing. Then matching and matching the historical monitoring data of the thermal runaway of the energy storage battery pack with a plurality of first gas concentration information sequences, a plurality of second gas concentration information sequences and a plurality of third gas concentration information sequences by taking the historical monitoring data of the thermal runaway of the energy storage battery pack as reference data, recording the data matched with the historical monitoring data of the thermal runaway of the energy storage battery pack as a sample first gas concentration information sequence, a sample second gas concentration information sequence and a sample third gas concentration information sequence, further, matching and matching the gas concentration data in the sample first gas concentration information sequence, the gas concentration data in the sample second gas concentration information sequence and the gas concentration data in the sample third gas concentration information sequence by a statistical algorithm, the method comprises the steps of obtaining and recording the change rules and trends of a first gas concentration information sequence, a second gas concentration information sequence and a third gas concentration information sequence of a sample, presetting the change trends of the first gas concentration, the second gas concentration and the third gas concentration, calculating the concentrations of hydrogen, carbon dioxide and carbon monoxide in each battery block in an energy storage battery pack respectively according to the preset first gas concentration, the second gas concentration and the third gas concentration by taking the preset first gas concentration, the second gas concentration and the third gas concentration as references, obtaining a plurality of first concentration correlation information of the first gas concentration information sequence, a plurality of second concentration correlation information of the second gas concentration information sequence and a plurality of third concentration correlation information of the third gas concentration information sequence, and simultaneously carrying out weighted calculation on the first concentration correlation information, the second concentration correlation information and the third concentration correlation information, namely, firstly distributing the first concentration correlation information, the second concentration correlation information and the third concentration correlation information with weight, and obtaining a plurality of first concentration correlation information, a plurality of second concentration correlation information and a plurality of third concentration correlation information weight, wherein the first concentration information and the third concentration information can be a plurality of concentration ratio of influence correlation coefficients: the second influence coefficient is 2:5:3, the influence parameters after the weighted calculation process are respectively the first influence parameter 0.2, the second influence parameter 0.5 and the second influence parameter 0.3, a plurality of concentration correlation information are obtained according to the weighted calculation result, the hydrogen concentration correlation, the carbon dioxide concentration correlation and the carbon monoxide concentration correlation in the energy storage battery pack reflected in the concentration correlation information are taken as analysis basic data, the thermal runaway of the energy storage battery pack is subjected to traceable analysis, namely, a plurality of sample concentration correlation information sets are firstly obtained based on historical monitoring data of the thermal runaway of the energy storage battery pack, each sample concentration correlation information set comprises a plurality of sample battery units in the energy storage battery pack and a plurality of sample concentration correlation information thereof, further, performing thermal runaway tracing monitoring on historical tracing detection data of thermal runaway of the energy storage battery pack according to tracing thermal runaway occurrence sequences of a plurality of sample battery cells, respectively performing thermal runaway tracing on a plurality of battery cells contained in the energy storage battery pack to determine a plurality of sample second tracing rating sets, taking tracing ratings of battery cells which are first subjected to thermal runaway in the energy storage battery pack as the highest level, performing similar sorting on tracing detection data in the historical tracing detection data of the thermal runaway of the energy storage battery pack, taking the sorted data sets as a plurality of sample second tracing rating sets, further, adopting a plurality of sample concentration correlation degree information sets and a plurality of sample second tracing rating sets as training data, correspondingly setting monitoring data through the training data, inputting the training data into a second tracing analysis channel to perform output monitoring adjustment, and when the output result of the second traceability analysis channel is consistent with the supervision data, finishing the training of the current group, finishing the training of all training data of the training, and finishing the training of the second traceability analysis channel.
In order to ensure the convergence and accuracy of the second traceability analysis channel, the convergence process may be that when a plurality of sample concentration correlation information sets and a plurality of sample second traceability rating sets in the second traceability analysis channel converge at one point, the convergence is performed when the second traceability analysis channel approaches to a certain value, the accuracy of the second traceability analysis channel can be tested through a test data set, for example, the test accuracy can be set to 80%, and when the test accuracy of the test data set meets 80%, the construction of the second traceability analysis channel is completed.
And finally, a plurality of second traceability ratings are obtained by inputting the concentration relativity information into a second traceability analysis channel, so that the thermal runaway of the energy storage battery pack is monitored and traced in the later period to serve as reference data.
Step A600: and calculating and obtaining the tracing ratings of the battery units based on the first tracing ratings and the second tracing ratings, and outputting tracing results according to the tracing ratings.
Further, step a600 of the present application further includes:
step a610: based on the first tracing ratings and the second tracing ratings, obtaining tracing ratings of the battery units through weighted calculation;
Step a620: and outputting a tracing result according to the plurality of tracing ratings, wherein the tracing result comprises a tracing battery unit, and the tracing rating corresponding to the tracing battery unit is the maximum value.
In the application, through the first traceability ratings output by the first traceability analysis channel and the second traceability ratings output by the second traceability analysis channel, more accurate monitoring traceability is performed when the energy storage battery pack has thermal runaway hidden danger, namely, the first traceability ratings and the second traceability ratings are used as traceability judgment basic data, the first traceability ratings and the second traceability ratings are weighted, and the weight ratio of the first traceability ratings and the second traceability ratings can be a first influence coefficient: and if the second influence coefficient is 7:3, the influence parameters after the weighted calculation process are respectively the first influence parameter 0.7, the second influence parameter 0.3, a plurality of tracing grades of a plurality of battery units are obtained according to the weighted calculation result, the tracing grades are used as judging basis for tracing the thermal runaway of the energy storage battery unit, the tracing grade of the battery unit which first generates the thermal runaway in the energy storage battery unit is regarded as the highest grade in the tracing grades, all battery units in the energy storage battery unit are correspondingly marked with tracing grades, the thermal runaway tracing data corresponding to the energy storage battery unit formed by the battery units with the tracing grades are recorded as tracing results and output, the tracing result comprises the tracing battery unit, the tracing battery unit is in corresponding relation with any battery unit in the energy storage battery unit, and the tracing grade corresponding to the tracing battery unit is the highest grade, so that the tracing grade of the thermal runaway of the energy storage battery unit is the highest grade, and the thermal runaway of the energy storage battery unit is monitored in the later stage.
In summary, the method for monitoring and tracing thermal runaway of the energy storage battery pack provided by the embodiment of the application at least comprises the following technical effects, so that the rationalized and accurate monitoring and tracing of the thermal runaway of the energy storage battery pack is realized, and the situation that the thermal runaway of the energy storage battery pack occurs is reduced.
Example two
Based on the same inventive concept as the method for monitoring and tracing thermal runaway of an energy storage battery pack in the foregoing embodiments, as shown in fig. 4, the present application provides a system for monitoring and tracing thermal runaway of an energy storage battery pack, the system includes:
the first judging module 1 is used for acquiring temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack through the temperature sensor array and the gas sensor array based on the thermal runaway monitoring module and the thermal runaway judging module, and judging potential thermal runaway hazards according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases;
the sequence acquisition module 2 is used for acquiring a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window when the first discrimination result is yes;
The second judging module 3 is used for carrying out early-stage matching judgment of thermal runaway according to the temperature information sequences and the air pressure information sequences in the air information sequences and a preset temperature change trend and a preset air pressure change trend to obtain a second judging result;
the first analysis module 4 is configured to extract, when the second determination result is yes, time information that the temperatures or the air pressures of the plurality of battery cells reach the temperature threshold or the air pressure threshold, and a plurality of matching degrees of the plurality of temperature information sequences and the plurality of air pressure information sequences with the preset temperature variation trend and the preset air pressure variation trend through the thermal runaway tracing module, and perform thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information, so as to obtain a plurality of first tracing ratings;
the second analysis module 5 is configured to extract a plurality of gas concentration information sequence sets in the plurality of gas information sequences, perform thermal runaway traceability analysis on gas concentration changes according to a plurality of preset gas concentration change trends of the plurality of specified gases, and obtain a plurality of second traceability ratings;
the calculating module 6 is configured to calculate and obtain the traceability ratings of the plurality of battery units based on the plurality of first traceability ratings and the plurality of second traceability ratings, and output traceability results according to the plurality of traceability ratings.
Further, the system further comprises:
the information acquisition module is used for continuously acquiring temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack through the temperature sensor array and the gas sensor array and acquiring gas pressure information in the gas information;
the threshold value acquisition module is used for acquiring a temperature threshold value and a barometric pressure threshold value based on historical detection data of the thermal runaway early stage of the energy storage battery pack;
the first judging module is used for judging whether any one piece of temperature information or any piece of air pressure information is larger than or equal to the temperature threshold value or the air pressure threshold value respectively, and obtaining a first judging result.
Further, the system further comprises:
the first fitting module is used for obtaining a plurality of temperature change curves and a plurality of air pressure change curves in a fitting mode by adopting a least square method based on the plurality of temperature information sequences and the plurality of air pressure information sequences;
the first calculation module is used for acquiring a plurality of sample temperature information sequences and a plurality of sample air pressure information sequences which are in thermal runaway based on historical detection data of the early phase of the thermal runaway of the energy storage battery pack, and calculating to acquire a preset temperature information sequence and a preset air pressure information sequence;
The second fitting module is used for fitting and obtaining the preset temperature change trend and the preset air pressure change trend based on the preset temperature information sequence and the preset air pressure information sequence;
the second calculation module is used for calculating the correlation degree of the temperature change curves and the air pressure change curves, the preset temperature change trend and the preset air pressure change trend respectively, obtaining a plurality of temperature correlation degree information and a plurality of air pressure correlation degree information, and calculating the correlation degree through the following formula:
;
wherein g is the correlation, M is the number of coordinate points in a temperature change curve or an air pressure change curve,is the temperature value or the air pressure value of the ith coordinate point in the temperature change curve or the air pressure change curve,/>A preset temperature value or a preset air pressure value of an ith coordinate point in a preset temperature change trend or a preset air pressure change trend, < ->And->The temperature change curve or the average temperature value or the average air pressure value in the air pressure change curve, and the average preset temperature value or the average preset air pressure value in the preset temperature change trend or the preset air pressure change trend;
and the second judging module is used for respectively judging whether any one of the temperature correlation information or any one of the air pressure correlation information is greater than or equal to a correlation threshold value or not to obtain a second judging result.
Further, the system further comprises:
the third judging module is used for detecting and judging the time when the temperature or the air pressure of the plurality of battery units reaches the temperature threshold value and the air pressure threshold value through the temperature sensor array and the air sensor array when the second judging result is yes, obtaining a plurality of time information, and sequencing according to the sequence from front to back to obtain a plurality of sequencing information;
the third calculation module is used for calculating a plurality of temperature information sequences and a plurality of air pressure information sequences, and a plurality of temperature correlation information and a plurality of air pressure correlation information of the preset temperature change trend and the preset air pressure change trend;
the weighting calculation module is used for carrying out weighting calculation on the temperature correlation information and the air pressure correlation information to obtain matching degrees;
and the control traceability analysis module is used for carrying out thermal runaway traceability analysis by combining a plurality of sequencing information and a plurality of matching degrees to obtain a plurality of first traceability ratings.
Further, the system further comprises:
the first set acquisition module is used for acquiring a plurality of sample ordering information sets and a plurality of sample matching degree information sets based on historical monitoring data of thermal runaway of the energy storage battery pack, and each sample ordering information set comprises a plurality of sample ordering information of a plurality of sample battery units;
The second set acquisition module is used for acquiring a plurality of sample first tracing rating sets according to the tracing thermal runaway occurrence sequence of the plurality of sample battery cells based on the historical tracing detection data of the thermal runaway of the energy storage battery pack;
the first channel module is used for training a converged first traceability analysis channel by adopting a plurality of sample sequencing information sets, a plurality of sample matching degree information sets and a plurality of sample first traceability rating sets as training data;
the first input module is used for acquiring a plurality of first traceability ratings, and the first traceability ratings are acquired by inputting a plurality of sequencing information and a plurality of matching degrees into a first traceability analysis channel.
Further, the system further comprises:
the first sequence extraction module is used for extracting and obtaining a plurality of first gas concentration information sequences, a plurality of second gas concentration information sequences and a plurality of third gas concentration information sequences in the plurality of gas information sequences according to the types of the plurality of specified gases, wherein the plurality of specified gases comprise hydrogen, carbon dioxide and carbon monoxide;
the second sequence extraction module is used for acquiring a first gas concentration information sequence of a sample, a second gas concentration information sequence of the sample and a third gas concentration information sequence of the sample based on historical monitoring data of thermal runaway of the energy storage battery pack;
The third fitting module is used for fitting to obtain a preset first gas concentration change trend, a preset second gas concentration change trend and a preset third gas concentration change trend based on the first gas concentration information sequence, the second gas concentration information sequence and the third gas concentration information sequence;
the fourth calculation module is used for calculating and obtaining a plurality of first concentration correlation degree information, a plurality of second concentration correlation degree information and a plurality of third concentration correlation degree information of the plurality of first gas concentration information sequences, the plurality of second gas concentration information sequences and the plurality of third gas concentration information sequences by taking the preset first gas concentration change trend, the second gas concentration change trend and the third gas concentration change trend as references, and weighting and calculating to obtain a plurality of concentration correlation degree information;
and the first rating module is used for performing thermal runaway traceability analysis according to the concentration relativity information to obtain a plurality of second traceability ratings.
Further, the system further comprises:
a third set acquisition module, configured to acquire a plurality of sample concentration correlation information sets based on historical monitoring data of thermal runaway of the energy storage battery pack, where each sample concentration correlation information set includes a plurality of sample concentration correlation information of a plurality of sample battery cells;
The fourth set acquisition module is used for acquiring a plurality of sample second traceability rating sets according to the traceability thermal runaway occurrence sequence of the plurality of sample battery cells based on historical traceability detection data of the thermal runaway of the energy storage battery pack;
the training module is used for training a converged second traceability analysis channel by adopting the plurality of sample concentration correlation degree information sets and the plurality of sample second traceability rating sets as training data;
the second rating module is used for acquiring a plurality of second traceability ratings, and the plurality of second traceability ratings are acquired by inputting a plurality of concentration relevance information into the second traceability analysis channel.
Further, the system further comprises:
the fifth calculation module is used for obtaining a plurality of traceability ratings of a plurality of battery units through weighted calculation based on the plurality of first traceability ratings and the plurality of second traceability ratings;
and the third rating module is used for outputting a tracing result according to the plurality of tracing ratings, wherein the tracing result comprises a tracing battery unit, and the tracing rating corresponding to the tracing battery unit is the maximum value.
The foregoing detailed description of a method for monitoring and tracing thermal runaway of an energy storage battery pack will be clear to those skilled in the art, and the device disclosed in this embodiment is relatively simple to describe, and relevant places refer to the description of the method section.
In one embodiment, a computer readable storage medium is provided, the computer device may be a server, and the internal structure of the computer device may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing news data, time attenuation factors and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to realize a thermal runaway monitoring and tracing method for the energy storage battery pack.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (4)
1. The utility model provides a thermal runaway monitoring traceability method of energy storage battery group, its characterized in that, the method is applied to an energy storage battery group thermal runaway monitoring traceability device, the device includes temperature sensor array and the gas sensor array of arranging a plurality of battery cells in the energy storage battery group to reach thermal runaway monitoring module, thermal runaway judgement module and thermal runaway traceability module, the method includes:
Based on a thermal runaway monitoring module and a thermal runaway judging module, acquiring temperature information and gas information of a plurality of battery power supplies in an energy storage battery pack through a temperature sensor array and a gas sensor array, and judging the hidden danger of the thermal runaway according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases;
when the first judging result is yes, collecting a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window;
according to the temperature information sequences and the air pressure information sequences in the air information sequences, performing early-stage matching judgment of thermal runaway according to a preset temperature change trend and a preset air pressure change trend, and obtaining a second judgment result;
when the second judging result is yes, extracting time information that the temperature or the air pressure of the plurality of battery cells reaches the temperature threshold or the air pressure threshold and a plurality of temperature information sequences and a plurality of matching degrees of the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend through a thermal runaway tracing module, and carrying out thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades;
Extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings;
based on the first tracing ratings and the second tracing ratings, calculating to obtain tracing ratings of the battery units, and outputting tracing results according to the tracing ratings;
and performing early-phase matching discrimination of thermal runaway according to the temperature change trend and the air pressure change trend to obtain a second discrimination result, wherein the early-phase matching discrimination of thermal runaway is performed according to the temperature information sequences and the air pressure information sequences in the air pressure information sequences, and the discrimination result comprises:
based on the temperature information sequences and the air pressure information sequences, adopting a least square method to obtain a plurality of temperature change curves and a plurality of air pressure change curves in a fitting way;
based on historical detection data of early thermal runaway of the energy storage battery pack, acquiring a plurality of sample temperature information sequences and a plurality of sample air pressure information sequences of the thermal runaway, and calculating to acquire a preset temperature information sequence and a preset air pressure information sequence;
fitting to obtain the preset temperature change trend and the preset air pressure change trend based on the preset temperature information sequence and the preset air pressure information sequence;
Calculating the correlation degree of the temperature change curves and the air pressure change curves with the preset temperature change trend and the preset air pressure change trend respectively to obtain a plurality of temperature correlation degree information and a plurality of air pressure correlation degree information, wherein the correlation degree is calculated by the following formula:
;
wherein g is the correlation, M is the number of coordinate points in a temperature change curve or an air pressure change curve,is the temperature value or the air pressure value of the ith coordinate point in the temperature change curve or the air pressure change curve,/>A preset temperature value or a preset air pressure value of an ith coordinate point in a preset temperature change trend or a preset air pressure change trend, < ->And->The temperature change curve or the average temperature value or the average air pressure value in the air pressure change curve, and the average preset temperature value or the average preset air pressure value in the preset temperature change trend or the preset air pressure change trend;
judging whether any one temperature correlation degree information or any one air pressure correlation degree information is larger than or equal to a correlation degree threshold value or not respectively to obtain a second judging result;
and when the second discrimination result is yes, extracting, by the thermal runaway tracing module, time information that the temperatures or air pressures of the plurality of battery cells reach the temperature threshold or the air pressure threshold, and a plurality of temperature information sequences and a plurality of matching degrees of the plurality of air pressure information sequences and the preset temperature variation trend and the preset air pressure variation trend, performing thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information, and obtaining a plurality of first tracing ratings, including:
When the second judging result is yes, detecting and judging the time when the temperature or the air pressure of the plurality of battery units reaches the temperature threshold value and the air pressure threshold value through the temperature sensor array and the air sensor array to obtain a plurality of time information, and sequencing according to the sequence from front to back to obtain a plurality of sequencing information;
calculating a plurality of temperature information sequences and a plurality of air pressure information sequences, and a plurality of temperature correlation information and a plurality of air pressure correlation information of the preset temperature variation trend and the preset air pressure variation trend;
weighting calculation is carried out on the temperature correlation information and the air pressure correlation information to obtain matching degrees;
the method comprises the steps of combining a plurality of sequencing information and a plurality of matching degrees, performing thermal runaway traceability analysis to obtain a plurality of first traceability ratings, combining the plurality of sequencing information and the plurality of matching degrees, performing the thermal runaway traceability analysis, and obtaining the plurality of first traceability ratings comprises: acquiring a plurality of sample ordering information sets and a plurality of sample matching degree information sets based on historical monitoring data of thermal runaway of the energy storage battery pack, wherein each sample ordering information set comprises a plurality of sample ordering information of a plurality of sample battery units; acquiring a first traceability rating set of a plurality of samples according to the traceability thermal runaway occurrence sequence of the plurality of sample battery cells based on historical traceability detection data of the thermal runaway of the energy storage battery pack; a plurality of sample ordering information sets, a plurality of sample matching degree information sets and a plurality of sample first traceability rating sets are adopted as training data to train a converged first traceability analysis channel; acquiring a plurality of first traceability ratings, and inputting a plurality of sorting information and a plurality of matching degrees into a first traceability analysis channel to acquire the first traceability ratings;
Extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, performing thermal runaway tracing analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases, and obtaining a plurality of second tracing ratings, including:
extracting and obtaining a plurality of first gas concentration information sequences, a plurality of second gas concentration information sequences and a plurality of third gas concentration information sequences in the plurality of gas information sequences according to the types of the plurality of specified gases, wherein the plurality of specified gases comprise hydrogen, carbon dioxide and carbon monoxide;
acquiring a first gas concentration information sequence of a sample, a second gas concentration information sequence of the sample and a third gas concentration information sequence of the sample based on historical monitoring data of thermal runaway of the energy storage battery pack;
fitting to obtain a preset first gas concentration change trend, a preset second gas concentration change trend and a preset third gas concentration change trend based on the sample first gas concentration information sequence, the sample second gas concentration information sequence and the sample third gas concentration information sequence;
calculating and obtaining a plurality of first concentration correlation information, a plurality of second concentration correlation information and a plurality of third concentration correlation information of the plurality of first gas concentration information sequences, the plurality of second gas concentration information sequences and the plurality of third gas concentration information sequences by taking the preset first gas concentration change trend, the second gas concentration change trend and the third gas concentration change trend as references, and weighting and calculating to obtain a plurality of concentration correlation information;
According to a plurality of concentration relevance information, carry out thermal runaway traceability analysis, obtain a plurality of second traceability grades, according to a plurality of concentration relevance information, carry out thermal runaway traceability analysis, obtain a plurality of second traceability grades and include: acquiring a plurality of sample concentration correlation information sets based on historical monitoring data of thermal runaway of the energy storage battery pack, wherein each sample concentration correlation information set comprises a plurality of sample concentration correlation information of a plurality of sample battery units; acquiring a second traceability rating set of a plurality of samples according to the traceability thermal runaway occurrence sequence of the plurality of sample battery cells based on historical traceability detection data of the thermal runaway of the energy storage battery pack; the plurality of sample concentration correlation degree information sets and the plurality of sample second traceability rating sets are adopted as training data to train a converged second traceability analysis channel; acquiring a plurality of second traceability ratings, wherein the plurality of second traceability ratings are acquired by inputting a plurality of concentration relevance information into the second traceability analysis channel;
based on a plurality of first traceability grades and a plurality of second traceability grades, calculate and obtain the traceability grades of a plurality of battery units to output traceability results according to a plurality of traceability grades, include:
Based on the first tracing ratings and the second tracing ratings, obtaining tracing ratings of the battery units through weighted calculation;
and outputting a tracing result according to the plurality of tracing ratings, wherein the tracing result comprises a tracing battery unit, and the tracing rating corresponding to the tracing battery unit is the maximum value.
2. The method according to claim 1, characterized in that the method comprises:
continuously acquiring temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack through the temperature sensor array and the gas sensor array, and acquiring gas pressure information in the gas information;
acquiring a temperature threshold and a barometric pressure threshold based on historical detection data of the energy storage battery pack in an early thermal runaway period;
and respectively judging whether any one of the temperature information or any one of the air pressure information is greater than or equal to the temperature threshold or the air pressure threshold, and obtaining a first judging result.
3. An energy storage battery thermal runaway monitoring and tracing system, the system being applied to the method of any one of claims 1-2, the system comprising:
the first judging module is used for acquiring temperature information and gas information of a plurality of battery power supplies in the energy storage battery pack through the temperature sensor array and the gas sensor array based on the thermal runaway monitoring module and the thermal runaway judging module, and judging potential thermal runaway hazards according to a temperature threshold value and a gas pressure threshold value to obtain a first judging result, wherein the gas information comprises gas pressure and gas concentration information of a plurality of specified gases;
The sequence acquisition module is used for acquiring a plurality of temperature information sequences and a plurality of gas information sequences of a plurality of battery power supplies in a rated time window when the first discrimination result is yes;
the second judging module is used for carrying out early-stage matching judgment of thermal runaway according to the temperature information sequences and the air pressure information sequences in the air information sequences and the preset temperature change trend and the preset air pressure change trend to obtain a second judging result;
the first analysis module is used for extracting time information that the temperature or the air pressure of the plurality of battery units reach the temperature threshold or the air pressure threshold through the thermal runaway tracing module when the second judging result is yes, and a plurality of matching degrees of the plurality of temperature information sequences and the plurality of air pressure information sequences and the preset temperature change trend and the preset air pressure change trend, and performing thermal runaway tracing analysis based on the plurality of matching degrees of the plurality of time information to obtain a plurality of first tracing grades;
the second analysis module is used for extracting a plurality of gas concentration information sequence sets in the plurality of gas information sequences, and performing thermal runaway traceability analysis on gas concentration change according to a plurality of preset gas concentration change trends of the plurality of specified gases to obtain a plurality of second traceability ratings;
The calculation module is used for calculating and obtaining the traceability ratings of the battery units based on the first traceability ratings and the second traceability ratings and outputting traceability results according to the traceability ratings;
the second discriminating module includes:
the first fitting module is used for obtaining a plurality of temperature change curves and a plurality of air pressure change curves in a fitting mode by adopting a least square method based on the plurality of temperature information sequences and the plurality of air pressure information sequences;
the first calculation module is used for acquiring a plurality of sample temperature information sequences and a plurality of sample air pressure information sequences which are in thermal runaway based on historical detection data of the early phase of the thermal runaway of the energy storage battery pack, and calculating to acquire a preset temperature information sequence and a preset air pressure information sequence;
the second fitting module is used for fitting and obtaining the preset temperature change trend and the preset air pressure change trend based on the preset temperature information sequence and the preset air pressure information sequence;
the second calculation module is used for calculating the correlation degree of the temperature change curves and the air pressure change curves, the preset temperature change trend and the preset air pressure change trend respectively, obtaining a plurality of temperature correlation degree information and a plurality of air pressure correlation degree information, and calculating the correlation degree through the following formula:
;
Wherein g is the correlation, M is the number of coordinate points in a temperature change curve or an air pressure change curve,is the temperature value or the air pressure value of the ith coordinate point in the temperature change curve or the air pressure change curve,/>A preset temperature value or a preset air pressure value of an ith coordinate point in a preset temperature change trend or a preset air pressure change trend, < ->And->For the average temperature value or average pressure value in the temperature or pressure curve, andsetting an average preset temperature value or an average preset air pressure value in a temperature change trend or a preset air pressure change trend;
and the second judging module is used for respectively judging whether any one of the temperature correlation information or any one of the air pressure correlation information is greater than or equal to a correlation threshold value or not to obtain a second judging result.
4. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 2 when the computer program is executed.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311378203.XA CN117117356B (en) | 2023-10-24 | 2023-10-24 | Energy storage battery pack thermal runaway monitoring and tracing method and system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311378203.XA CN117117356B (en) | 2023-10-24 | 2023-10-24 | Energy storage battery pack thermal runaway monitoring and tracing method and system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN117117356A CN117117356A (en) | 2023-11-24 |
CN117117356B true CN117117356B (en) | 2024-03-12 |
Family
ID=88800606
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311378203.XA Active CN117117356B (en) | 2023-10-24 | 2023-10-24 | Energy storage battery pack thermal runaway monitoring and tracing method and system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117117356B (en) |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111391668A (en) * | 2020-03-31 | 2020-07-10 | 威睿电动汽车技术(宁波)有限公司 | Battery thermal runaway early warning processing method, device, equipment and storage medium |
CN112731159A (en) * | 2020-12-23 | 2021-04-30 | 江苏省电力试验研究院有限公司 | Method for pre-judging and positioning battery fault of battery compartment of energy storage power station |
CN112731169A (en) * | 2020-12-22 | 2021-04-30 | 上汽大众汽车有限公司 | All-weather monitoring system and method for thermal runaway of power battery |
CN113442725A (en) * | 2021-04-30 | 2021-09-28 | 重庆长安汽车股份有限公司 | Power battery thermal runaway alarm method and system and vehicle |
CN114240260A (en) * | 2022-02-17 | 2022-03-25 | 北京航空航天大学 | New energy group vehicle thermal runaway risk assessment method based on digital twinning |
CN114624609A (en) * | 2022-04-01 | 2022-06-14 | 阳光储能技术有限公司 | Battery thermal runaway detection method and device |
CN114824537A (en) * | 2022-06-30 | 2022-07-29 | 深圳市明泰源科技有限公司 | Lithium iron phosphate battery thermal runaway monitoring system based on information fusion |
CN115995625A (en) * | 2022-11-08 | 2023-04-21 | 浙江凌骁能源科技有限公司 | Battery thermal runaway early warning method, device and storage medium |
CN116256651A (en) * | 2023-02-01 | 2023-06-13 | 欣旺达电动汽车电池有限公司 | Battery thermal incapacitation early warning method, system and readable storage medium |
CN116796285A (en) * | 2023-06-05 | 2023-09-22 | 山东大学 | Power battery thermal runaway advanced early warning method and system based on multi-source information fusion |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20210116050A (en) * | 2020-03-17 | 2021-09-27 | 주식회사 엘지에너지솔루션 | Apparatus and method for battery abnormal condition prediction, and battery management system providing the same method |
-
2023
- 2023-10-24 CN CN202311378203.XA patent/CN117117356B/en active Active
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111391668A (en) * | 2020-03-31 | 2020-07-10 | 威睿电动汽车技术(宁波)有限公司 | Battery thermal runaway early warning processing method, device, equipment and storage medium |
CN112731169A (en) * | 2020-12-22 | 2021-04-30 | 上汽大众汽车有限公司 | All-weather monitoring system and method for thermal runaway of power battery |
CN112731159A (en) * | 2020-12-23 | 2021-04-30 | 江苏省电力试验研究院有限公司 | Method for pre-judging and positioning battery fault of battery compartment of energy storage power station |
CN113442725A (en) * | 2021-04-30 | 2021-09-28 | 重庆长安汽车股份有限公司 | Power battery thermal runaway alarm method and system and vehicle |
CN114240260A (en) * | 2022-02-17 | 2022-03-25 | 北京航空航天大学 | New energy group vehicle thermal runaway risk assessment method based on digital twinning |
CN114624609A (en) * | 2022-04-01 | 2022-06-14 | 阳光储能技术有限公司 | Battery thermal runaway detection method and device |
CN114824537A (en) * | 2022-06-30 | 2022-07-29 | 深圳市明泰源科技有限公司 | Lithium iron phosphate battery thermal runaway monitoring system based on information fusion |
CN115995625A (en) * | 2022-11-08 | 2023-04-21 | 浙江凌骁能源科技有限公司 | Battery thermal runaway early warning method, device and storage medium |
CN116256651A (en) * | 2023-02-01 | 2023-06-13 | 欣旺达电动汽车电池有限公司 | Battery thermal incapacitation early warning method, system and readable storage medium |
CN116796285A (en) * | 2023-06-05 | 2023-09-22 | 山东大学 | Power battery thermal runaway advanced early warning method and system based on multi-source information fusion |
Also Published As
Publication number | Publication date |
---|---|
CN117117356A (en) | 2023-11-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN114559819B (en) | Electric automobile battery safety early warning method based on signal processing | |
CN116502112B (en) | New energy power supply test data management method and system | |
CN112906744A (en) | Fault single battery identification method based on isolated forest algorithm | |
CN112327167A (en) | Battery capacity diving risk assessment method and system | |
CN113866642A (en) | Lithium ion battery fault diagnosis method based on gradient lifting tree | |
CN112816881B (en) | Battery pressure difference abnormality detection method, device and computer storage medium | |
CN111273125A (en) | RST-CNN-based power cable channel fault diagnosis method | |
CN115267555A (en) | Battery SOH (State of health) evaluation system of energy storage system based on battery multipoint temperature measurement | |
CN116466237B (en) | Charging safety monitoring and early warning method and system for lithium battery | |
CN116572747B (en) | Battery fault detection method, device, computer equipment and storage medium | |
CN114994547B (en) | Battery pack safety state evaluation method based on deep learning and consistency detection | |
CN114734873B (en) | Power battery monomer thermal runaway early warning method based on cloud online data | |
CN117148194A (en) | Electric automobile battery pack fault detection method and system | |
CN113253125B (en) | Information fusion-based lithium iron phosphate battery thermal runaway monitoring method and system | |
CN115494400A (en) | Lithium battery lithium separation state online monitoring method based on ensemble learning | |
CN114280490B (en) | Lithium ion battery state of charge estimation method and system | |
CN114036647A (en) | Power battery safety risk assessment method based on real vehicle data | |
CN117525692B (en) | Control method and system of safe energy storage system | |
CN116923188B (en) | Charging protection system of new energy vehicle | |
Diao et al. | Research on Electric Vehicle Charging Safety Warning Based on A-LSTM Algorithm | |
CN117117356B (en) | Energy storage battery pack thermal runaway monitoring and tracing method and system | |
CN117491813A (en) | Insulation abnormality detection method for power battery system of new energy automobile | |
CN117216956A (en) | Device, method and equipment for correcting thermal-oxidative aging model of XLPE cable | |
CN116796285A (en) | Power battery thermal runaway advanced early warning method and system based on multi-source information fusion | |
CN115469226A (en) | Real-time safety early warning method for electric vehicle power battery based on operation big data |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |